Nutritional manipulations in the perinatal period program adipose tissue in offspring
Bibliographic record
Abstract
Epidemiological studies demonstrated initially that maternal undernutrition results in low birth weight with increased risk for long-lasting energy balance disorders. Maternal obesity and diabetes associated with high birth weight, excessive nutrition in neonates, and rapid catchup growth also increase the risk of adult-onset obesity. As stated by the Developmental Origin of Health and Disease concept, nutrient supply perturbations in the fetus or neonate result in long-term programming of individual body weight set point. Adipose tissue is a key fuel storage unit involved mainly in the maintenance of energy homeostasis. Studies in numerous animal models have demonstrated that the adipose tissue is the focus of developmental programming events in a sex- and depot-specific manner. In rodents, adipose tissue development is particularly active during the perinatal period, especially during the last week of gestation and during early postnatal life. In contrast to rodents, this process essentially takes place before birth in bigger mammals. Despite these different developmental time windows, altricial and precocial species share several mechanisms of adipose tissue programming. Offspring from malnourished dams present adipose tissue with a series of alterations: impaired glucose uptake, insulin and leptin resistance, low-grade inflammation, modified sympathetic activity with reduced noradrenergic innervations, and thermogenesis. These modifications reprogram adipose tissue metabolism by changing fat distribution and composition and by enhancing adipogenesis, predisposing the offspring to fat accumulation. Subtle adipose tissue circadian rhythm changes are also observed. Inappropriate hormone levels, modified tissue sensitivity (especially glucocorticoid system), and epigenetic mechanisms are key factors for adipose tissue programming during the perinatal period.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".